This notebook contains a set of analyses for analyzing Bbqturtle’s boardgamegeek collection. The bulk of the analysis is focused on building a user-specific predictive model to predict the games that the specified user is likely to own. This enables us to ask questions like, based on the games the user currently owns, what games are a good fit for their collection? What upcoming games are they likely to purchase?
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We can look at a basic description of the number of games that the user owns, has rated, has previously owned, etc.
What years has the user owned/rated games from? While we can’t see when a user added or removed a game from their collection, we can look at their collection by the years in which their games were published.
We can look at the most frequent types of categories, mechanics, designers, and artists that appear in a user’s collection.
We’ll examine a predictive model trained on a user’s collection for games published through 2020. How many games has the user owned/rated/played in the training set (games prior to 2020)?
username | dataset | period | games_owned | games_rated |
Bbqturtle | training | published before 2020 | 52 | 52 |
Bbqturtle | validation | published 2020 | 1 | 1 |
Bbqturtle | test | published after 2020 | 3 | 2 |
The main outcome we will be modeling for the user is owned, which refers to whether the user currently owns or has a previously owned a game in their collection. Our goal is to train a predictive model to learn the probability that a user will add a game to their collection based on its observable features.
We can examine coefficients from the model we trained, which is a logistic regression with elastic net regularization (which I will refer to as a penalized logistic regression). Positive values indicate that a feature increases a user’s probability of owning/rating a game, while negative values indicate a feature decreases the probability. To be precise, the coefficients indicate the effect of a particular feature on the log-odds of a user owning a game.
Why did the model identify these features? We can make density plots of the important features for predicting whether the user owned a game. Blue indicates the density for games owned by the user, while grey indicates the density for games not owned by the user.
Binary predictors can be difficult to see with this visualization, so we can also directly examine the percentage of games in a user’s collection with a predictor vs the percentage of all games with that predictor.
% of Games with Feature | ||||
username | Feature | In_Collection | All_Games | Ratio |
Bbqturtle | Days Of Wonder | 5.8% | 0.3% | 18.49 |
Bbqturtle | Space Cowboys | 5.8% | 0.3% | 18.49 |
Bbqturtle | Artist Chris Quilliams | 3.8% | 0.5% | 8.46 |
Bbqturtle | Artist Ian Otoole | 1.9% | 0.3% | 7.44 |
Bbqturtle | Enclosure | 7.7% | 1.1% | 7.19 |
Bbqturtle | Public Domain | 5.8% | 0.9% | 6.47 |
Bbqturtle | Artist Dennis Lohausen | 3.8% | 0.7% | 5.39 |
Bbqturtle | Ravensburger | 13.5% | 2.8% | 4.73 |
Bbqturtle | ZMan Games | 11.5% | 2.5% | 4.66 |
Bbqturtle | Pirates | 7.7% | 1.6% | 4.66 |
Bbqturtle | Wooden Pieces Boards | 5.8% | 1.3% | 4.46 |
Bbqturtle | Asmodee | 17.3% | 4.1% | 4.21 |
Bbqturtle | Artist Harald Lieske | 3.8% | 0.9% | 4.11 |
Bbqturtle | Negotiation | 13.5% | 3.4% | 4.00 |
Bbqturtle | Commodity Speculation | 5.8% | 1.5% | 3.85 |
Bbqturtle | Party Game | 32.7% | 8.5% | 3.84 |
Bbqturtle | Bluffing | 23.1% | 6.2% | 3.70 |
Bbqturtle | Tricktaking | 5.8% | 1.6% | 3.58 |
Bbqturtle | Racing | 9.6% | 2.9% | 3.37 |
Bbqturtle | Mayfair Games | 5.8% | 1.8% | 3.24 |
Bbqturtle | Eaglegryphon Games | 3.8% | 1.2% | 3.17 |
Bbqturtle | USA | 5.8% | 1.9% | 3.08 |
Bbqturtle | Hasbro | 9.6% | 3.5% | 2.77 |
Bbqturtle | Pegasus Spiele | 9.6% | 3.5% | 2.72 |
Bbqturtle | Murder Mystery | 0.0% | 1.6% | 0.00 |
Before predicting games in upcoming years, we can examine how well the model did and what games it liked in the training set. In this case, we used resampling techniques (cross validation) to ensure that the model had not seen a game before making its predictions.
An easy way to examine the performance of classification model is to view a separation plot. We plot the predicted probabilities from the model for every game (from resampling) from lowest to highest. We then overlay a blue line for any game that the user does own. A good classifier is one that is able to separate the blue (games owned by the user) from the white (games not owned by the user), with most of the blue occurring at the highest probabilities (right side of the chart).
We can display this information in table form, displaying the 100 games with the highest probability of ownership, adding a blue line when the user does own the game.
Rank | Published | ID | Name | Pr(Owned) | Owned |
1 | 2014 | 148228 | Splendor | 0.711 | no |
2 | 2006 | 22141 | Cleopatra and the Society of Architects | 0.684 | no |
3 | 2007 | 28023 | Jamaica | 0.619 | yes |
4 | 2004 | 9220 | Saboteur | 0.516 | no |
5 | 2014 | 152241 | Ultimate Werewolf | 0.514 | no |
6 | 2008 | 38159 | Ultimate Werewolf: Ultimate Edition | 0.514 | no |
7 | 2018 | 260428 | Pandemic: Fall of Rome | 0.393 | no |
8 | 2003 | 6068 | Queen's Necklace | 0.383 | no |
9 | 2015 | 165959 | Jolly Roger: The Game of Piracy & Mutiny | 0.355 | no |
10 | 2010 | 63740 | Hotel Samoa | 0.332 | no |
11 | 2017 | 219215 | Werewords | 0.327 | no |
12 | 1893 | 2386 | Chinese Checkers | 0.323 | no |
13 | 2019 | 265684 | Subtext | 0.301 | no |
14 | 2018 | 250878 | Rebel Nox | 0.292 | no |
15 | 2007 | 30324 | Ca$h 'n Gun$: Live | 0.285 | no |
16 | 2010 | 67148 | Ultimate Werewolf: Compact Edition | 0.278 | no |
17 | 2014 | 147949 | One Night Ultimate Werewolf | 0.277 | yes |
18 | 2015 | 163166 | One Night Ultimate Werewolf: Daybreak | 0.274 | yes |
19 | 2008 | 38318 | Start Player | 0.255 | no |
20 | 1998 | 2667 | What Were You Thinking? | 0.223 | no |
21 | 1986 | 925 | Werewolf | 0.218 | no |
22 | 2018 | 206715 | Ultimate Werewolf Legacy | 0.208 | no |
23 | 2019 | 270971 | Era: Medieval Age | 0.192 | no |
24 | 2016 | 192297 | America | 0.183 | no |
25 | 2018 | 251622 | Moneybags | 0.182 | no |
26 | 1989 | 1325 | Wild Pirates | 0.179 | no |
27 | 2017 | 204431 | One Night Ultimate Alien | 0.175 | no |
28 | 2012 | 93563 | Whitewater | 0.173 | no |
29 | 2019 | 271530 | Ankh'or | 0.168 | no |
30 | 2019 | 269725 | Corinth | 0.166 | no |
31 | 2017 | 230305 | Unlock!: Mystery Adventures – The Tonipal's Treasure | 0.166 | no |
32 | 2015 | 180956 | One Night Ultimate Vampire | 0.165 | yes |
33 | 2016 | 205125 | Ticket to Ride: First Journey (U.S.) | 0.161 | no |
34 | 2010 | 25292 | Merchants & Marauders | 0.158 | no |
35 | 2015 | 176458 | Rights | 0.153 | no |
36 | 2011 | 92415 | Skull | 0.152 | no |
37 | 2016 | 184919 | Greedy Greedy Goblins | 0.150 | no |
38 | -3000 | 2397 | Backgammon | 0.146 | no |
39 | 2017 | 224212 | Red Scare | 0.142 | no |
40 | 2013 | 172971 | Crossing | 0.137 | no |
41 | 2006 | 25738 | The Big Taboo | 0.132 | no |
42 | 2017 | 221107 | Pandemic Legacy: Season 2 | 0.131 | no |
43 | 2015 | 176361 | One Night Revolution | 0.130 | no |
44 | 2008 | 30549 | Pandemic | 0.129 | no |
45 | -2600 | 1602 | The Royal Game of Ur | 0.120 | no |
46 | 2012 | 124742 | Android: Netrunner | 0.120 | no |
47 | 400 | 2136 | Pachisi | 0.118 | no |
48 | 2011 | 98229 | Pictomania | 0.118 | no |
49 | 2014 | 169654 | Deep Sea Adventure | 0.116 | no |
50 | 2003 | 6979 | Match of the Penguins | 0.112 | no |
51 | 2011 | 118497 | Trick of the Rails | 0.110 | no |
52 | 2009 | 42244 | Martinique | 0.109 | no |
53 | 2019 | 255293 | One Night Ultimate Super Villains | 0.108 | no |
54 | 2018 | 244521 | The Quacks of Quedlinburg | 0.106 | no |
55 | 2006 | 25420 | Ur | 0.106 | no |
56 | 2013 | 143693 | Glass Road | 0.104 | no |
57 | 1530 | 7316 | Bingo | 0.103 | no |
58 | 2011 | 99132 | 2019: The ARCTIC | 0.103 | no |
59 | 2019 | 278553 | Silver | 0.099 | no |
60 | 2014 | 159581 | Maskmen | 0.097 | no |
61 | 2018 | 267945 | Mr. Face | 0.096 | no |
62 | 1991 | 11573 | Celebrity Taboo | 0.095 | no |
63 | 2017 | 225244 | Ticket to Ride: Germany | 0.095 | no |
64 | 2010 | 20437 | Lords of Vegas | 0.092 | no |
65 | 2014 | 159633 | Start Player Express | 0.091 | no |
66 | 2010 | 66081 | Pocket Battles: Elves vs. Orcs | 0.090 | no |
67 | 2007 | 31627 | Ticket to Ride: Nordic Countries | 0.090 | no |
68 | 2014 | 154125 | Pocket Battles: Confederacy vs Union | 0.088 | no |
69 | 1995 | 13 | Catan | 0.088 | no |
70 | 2014 | 158435 | Dogs of War | 0.087 | no |
71 | 1530 | 11028 | Lotto | 0.087 | no |
72 | 1999 | 920 | Ultimate Outburst | 0.087 | no |
73 | 2004 | 10630 | Memoir '44 | 0.086 | no |
74 | 1968 | 7262 | Top Trumps | 0.085 | no |
75 | 2004 | 10547 | Betrayal at House on the Hill | 0.084 | no |
76 | 2017 | 229006 | SpyNet | 0.083 | no |
77 | 2013 | 140468 | You Suck | 0.081 | no |
78 | 2012 | 103660 | VivaJava: The Coffee Game | 0.077 | no |
79 | 2016 | 177736 | A Feast for Odin | 0.076 | no |
80 | 1992 | 642 | Oodles | 0.076 | no |
81 | 1995 | 929 | The Great Dalmuti | 0.075 | no |
82 | 2007 | 32471 | Mafia | 0.075 | no |
83 | 2008 | 33911 | Bacchus' Banquet | 0.074 | no |
84 | 2018 | 252197 | One Week Ultimate Werewolf | 0.072 | no |
85 | 2006 | 25417 | BattleLore | 0.072 | no |
86 | 2008 | 47046 | Gambit 7 | 0.070 | no |
87 | 2006 | 27117 | Animalia | 0.070 | no |
88 | 2018 | 245382 | The Way of the Bear | 0.069 | no |
89 | 2007 | 27746 | Colosseum | 0.069 | no |
90 | 2014 | 160499 | King of New York | 0.067 | no |
91 | 2015 | 174893 | TROLL | 0.067 | no |
92 | 2019 | 289018 | On a Scale of One to T-Rex | 0.066 | no |
93 | 1998 | 22347 | Pecking Order | 0.065 | no |
94 | 2015 | 178570 | Unusual Suspects | 0.065 | no |
95 | 2019 | 272453 | KeyForge: Age of Ascension | 0.064 | no |
96 | 1999 | 204 | Stephenson's Rocket | 0.064 | no |
97 | 2017 | 215371 | CrossTalk | 0.064 | no |
98 | 2016 | 191982 | Knit Wit | 0.064 | no |
99 | 2019 | 142379 | Escape Plan | 0.063 | no |
100 | 2000 | 822 | Carcassonne | 0.063 | no |
We can also more formally assess how well the model did in resampling by looking at the area under the receiver operating characteristic. A perfect model would receive a score of 1, while a model that cannot predict the outcome will default to a score of 0.5. The extent to which something is a good score depends on the setting, but generally anything in the .8 to .9 range is very good while the .7 to .8 range is perfectly acceptable.
Another way to think about the model performance is to view its lift, or its ability to detect the positive outcomes over that of a null model. High lift indicates the model can much more quickly find all of the positive outcomes (in this case, games owned or played by the user), while a model with no lift is no better than random guessing. A gains chart is another way to view this.
Finally, we can understand the performance of the model by examining its calibration. If the model assigns a probability of 5%, how often does the outcome actually occur? A well calibrated model is one in which the predicted probabilities reflect the probabilities we would observe in the actual data. We can assess the calibration of a model by grouping its predictions into bins and assessing how often we observe the outcome versus how often our model expects to observe the outcome.
A model that is well calibrated will closely follow the dashed line - its expected probabilities match that of the observed probabilities. A model that consistently underestimates the probability of the event will be over this dashed line, be a while a model that overestimates the probability will be under the dashed line.
What games does the model think Bbqturtle is most likely to own that are not in their collection?
Published | ID | Name | Pr(Owned) | Owned |
2014 | 148228 | Splendor | 0.711 | no |
2006 | 22141 | Cleopatra and the Society of Architects | 0.684 | no |
2004 | 9220 | Saboteur | 0.516 | no |
2014 | 152241 | Ultimate Werewolf | 0.514 | no |
2008 | 38159 | Ultimate Werewolf: Ultimate Edition | 0.514 | no |
What games does the model think Bbqturtle is least likely to own that are in their collection?
Published | ID | Name | Pr(Owned) | Owned |
2014 | 154825 | Arkwright | 0.001 | yes |
2014 | 165722 | KLASK | 0.001 | yes |
2004 | 2651 | Power Grid | 0.001 | yes |
2018 | 249381 | The Estates | 0.001 | yes |
2013 | 137330 | Cube Quest | 0.001 | yes |
Top 25 games most likely to be owned by the user in each year, highlighting in blue the games that the user has owned.
rank | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 |
1 | Whitewater | Crossing | Splendor | Jolly Roger: The Game of Piracy & Mutiny | America | Werewords | Pandemic: Fall of Rome | Subtext |
2 | Android: Netrunner | Glass Road | Ultimate Werewolf | One Night Ultimate Werewolf: Daybreak | Ticket to Ride: First Journey (U.S.) | One Night Ultimate Alien | Rebel Nox | Era: Medieval Age |
3 | VivaJava: The Coffee Game | You Suck | One Night Ultimate Werewolf | One Night Ultimate Vampire | Greedy Greedy Goblins | Unlock!: Mystery Adventures – The Tonipal's Treasure | Ultimate Werewolf Legacy | Ankh'or |
4 | Ghost Blitz 2 | Kobayakawa | Deep Sea Adventure | Rights | A Feast for Odin | Red Scare | Moneybags | Corinth |
5 | Sky Tango | Cappuccino | Maskmen | One Night Revolution | Knit Wit | Pandemic Legacy: Season 2 | The Quacks of Quedlinburg | One Night Ultimate Super Villains |
6 | Escape: The Curse of the Temple | Mascarade | Start Player Express | TROLL | Robo Rally | Ticket to Ride: Germany | Mr. Face | Silver |
7 | The Resistance: Avalon | Animals Frightening Night! | Pocket Battles: Confederacy vs Union | Unusual Suspects | Pandemic: Reign of Cthulhu | SpyNet | One Week Ultimate Werewolf | On a Scale of One to T-Rex |
8 | Kingdom of Solomon | Carcassonne: South Seas | Dogs of War | 504 | Burke's Gambit | CrossTalk | The Way of the Bear | KeyForge: Age of Ascension |
9 | Archipelago | Corto | King of New York | Fool's Gold | Pandemic: Iberia | Pandemic: Rising Tide | Ticket to Ride: New York | Escape Plan |
10 | Rumble in the Dungeon | Room 25 | Pandemic: The Cure | Automania | Codenames: Pictures | Bunny Kingdom | Rising Sun | Trogdor!! The Board Game |
11 | Terra Mystica | Ghost Blitz: 5 to 12 | Pathfinder Adventure Card Game: Skull & Shackles – Base Set | Codenames | Citadels | Destination X | The River | Blue Banana |
12 | Mutant Meeples | Futterneid | Irish Gauge | The Gallerist | Turin Market | Kokoro: Avenue of the Kodama | Team UP! | Deep Blue |
13 | Suburbia | Tash-Kalar: Arena of Legends | Pictopia: Disney Edition | Mombasa | Capital Lux | The Palace of Mad King Ludwig | Illusion | Throw Throw Burrito |
14 | Pocket Battles: Macedonians vs. Persians | Rococo | Doodle City | Arboretum | Hive Mind | Codenames: Disney – Family Edition | Decrypto | Pipeline |
15 | Robinson Crusoe: Adventures on the Cursed Island | Pelican Bay | Colt Express | Treasure Hunter | Quadropolis | Downforce | Werewords Deluxe Edition | The Mind Extreme |
16 | Cockroach Poker Royal | Disc Duelers | Moral Dilemma | Mafia de Cuba | Camel Up Cards | That's a Question! | Orbis | Ninja Academy |
17 | Think Again! | Dread Curse | Castles of Mad King Ludwig | Unspeakable Words: Deluxe Edition | Agricola (Revised Edition) | Best of Werewolves of Miller's Hollow | Thornwatch | Caylus 1303 |
18 | Dixit Jinx | Wooolf!! | Black Fleet | Plums | Dead Last | Iberian Gauge | Brikks | Unlock!: Epic Adventures |
19 | Pirate Dice: Voyage on the Rolling Seas | Tomorrow | Ca$h 'n Guns (Second Edition) | Dead Man's Chest | Junk Art | Import / Export | Unlock!: Heroic Adventures | Codenames: The Simpsons |
20 | Clash of Cultures | Batman: Gotham City Strategy Game | Don't Mess with Cthulhu | T.I.M.E Stories | Vinhos Deluxe Edition | Oliver Twist | KeyForge: Call of the Archons | TIME Stories Revolution: Damien 1958 NT |
21 | Qin | Skull King | Sushi Dice | Brick Party | Ghost Blitz: Spooky Doo | Breaking Bad: The Board Game | That's Pretty Clever! | Fafnir |
22 | One Night Werewolf | Francis Drake | Chimera | Elysium | The Pyramid's Deadline | Unlock!: Escape Adventures – Doo-Arann Dungeon | Black Skull Island | Unlock!: Exotic Adventures – Expedition: Challenger |
23 | PIX | Rise of Augustus | Five Tribes | Het Koninkrijk Dominion | Simon's Cat Card Game | Miaui | Scarabya | Tonari |
24 | Mafia: Vendetta | Pathfinder Adventure Card Game: Rise of the Runelords – Base Set | Camel Up | Loop Inc. | Sabordage | Codenames: Marvel | Treasure Island | Twice as Clever! |
25 | Zug um Zug: Deutschland | Coal Baron | San Juan (Second Edition) | Booty | Krazy Wordz | Troika | Fireball Island: The Curse of Vul-Kar | Time Chase |
Interactive table for predictions from resampling.
We’ll validate the model by looking at its predictions for games published in 2020. That is, how well did a model trained on a user’s collection through 2020 perform in predicting games for the user in 2020?
username | outcome | dataset | method | .metric | .estimate |
Bbqturtle | owned | validation | glmnet | roc_auc | 0.833 |
Table of top 50 games from 2020, highlighting games that the user owns.
Published | ID | Name | Pr(Owned) | Owned |
2020 | 287158 | Half Truth | 0.120 | no |
2020 | 245658 | Unicorn Fever | 0.044 | no |
2020 | 309113 | Ticket to Ride: Amsterdam | 0.042 | no |
2020 | 300001 | Renature | 0.030 | no |
2020 | 324345 | キャットインザボックス (Cat in the box) | 0.029 | no |
2020 | 302926 | Silver Coin | 0.026 | no |
2020 | 318098 | Silver Dagger | 0.026 | no |
2020 | 301607 | KeyForge: Mass Mutation | 0.023 | no |
2020 | 283155 | Calico | 0.022 | no |
2020 | 286236 | Poisons | 0.021 | no |
2020 | 186986 | Kung Fu Panda: The Board Game | 0.021 | no |
2020 | 309630 | Small World of Warcraft | 0.020 | no |
2020 | 294232 | Stolen Paintings | 0.020 | no |
2020 | 299607 | Capital Lux 2: Generations | 0.020 | no |
2020 | 314040 | Pandemic Legacy: Season 0 | 0.020 | no |
2020 | 302425 | Unlock!: Mythic Adventures | 0.019 | no |
2020 | 312267 | Star Wars: Unlock! | 0.019 | no |
2020 | 327913 | Unlock!: Timeless Adventures – Arsène Lupin und der große weiße Diamant | 0.019 | no |
2020 | 297486 | Ride the Rails | 0.019 | no |
2020 | 271524 | TIME Stories Revolution: A Midsummer Night | 0.019 | no |
2020 | 287742 | TIME Stories Revolution: The Hadal Project | 0.019 | no |
2020 | 316546 | Clever Cubed | 0.018 | no |
2020 | 301919 | Pandemic: Hot Zone – North America | 0.017 | no |
2020 | 298638 | Sheriff of Nottingham: 2nd Edition | 0.015 | no |
2020 | 293296 | Splendor: Marvel | 0.015 | no |
2020 | 302463 | Telestrations: Upside Drawn | 0.015 | no |
2020 | 265784 | Cleopatra and the Society of Architects: Deluxe Edition | 0.014 | no |
2020 | 287033 | Gray Eminence | 0.014 | no |
2020 | 282171 | Trial by Trolley | 0.014 | no |
2020 | 319114 | Krazy Pix | 0.013 | no |
2020 | 284998 | Reigns: The Council | 0.013 | no |
2020 | 299592 | Beez | 0.013 | no |
2020 | 297892 | Dodelido Extreme | 0.013 | no |
2020 | 313531 | Rustling Leaves | 0.012 | no |
2020 | 273092 | Crumbs | 0.012 | no |
2020 | 294448 | Tea for 2 | 0.012 | no |
2020 | 303054 | Yacht Rock | 0.011 | no |
2020 | 313817 | Hello Neighbor: The Secret Neighbor Party Game | 0.011 | no |
2020 | 184267 | On Mars | 0.011 | no |
2020 | 299169 | Spicy | 0.011 | no |
2020 | 284378 | Kanban EV | 0.011 | no |
2020 | 294484 | Unmatched: Cobble & Fog | 0.010 | no |
2020 | 300936 | Via Magica | 0.010 | no |
2020 | 297139 | Potato Pirates: Enter the Spudnet | 0.010 | no |
2020 | 296626 | Sonora | 0.010 | no |
2020 | 245659 | Vampire: The Masquerade – Vendetta | 0.010 | no |
2020 | 325635 | Unmatched: Little Red Riding Hood vs. Beowulf | 0.010 | no |
2020 | 295687 | Trust Me, I'm a Doctor | 0.010 | no |
2020 | 317981 | Coyote | 0.010 | no |
2020 | 295486 | My City | 0.010 | no |
We can then refit our model to the training and validation set in order to predict all upcoming games for the user.
Examine the top 50 games for upcoming games, highlighting in blue ones the user already.
Published | ID | Name | Pr(Owned) | Owned |
2021 | 311920 | Ultimate Werewolf: Extreme | 0.156 | no |
2021 | 271529 | Botanik | 0.126 | no |
2022 | 356033 | Libertalia: Winds of Galecrest | 0.043 | no |
2021 | 339906 | The Hunger | 0.031 | no |
2022 | 345584 | Mindbug | 0.029 | no |
2021 | 332944 | Sobek: 2 Players | 0.028 | no |
2021 | 330401 | Dokojong | 0.027 | no |
2021 | 316287 | Quest | 0.025 | no |
2021 | 314421 | The Fuzzies | 0.025 | yes |
2021 | 329670 | Pandemic: Hot Zone – Europe | 0.023 | no |
2022 | 326945 | Castles of Mad King Ludwig: Collector's Edition | 0.022 | no |
2021 | 324856 | The Crew: Mission Deep Sea | 0.021 | no |
2021 | 301257 | Maglev Metro | 0.021 | no |
2021 | 316080 | KeyForge: Dark Tidings | 0.020 | no |
2021 | 330403 | Moon Adventure | 0.019 | no |
2022 | 349067 | The Lord of the Rings: The Card Game – Revised Core Set | 0.018 | no |
2021 | 316343 | Capital Lux 2: Pocket | 0.017 | no |
2022 | 349463 | Dungeons, Dice & Danger | 0.017 | no |
2022 | 322524 | Bardsung | 0.016 | no |
2021 | 350636 | Unlock!: Game Adventures | 0.016 | no |
2021 | 336794 | Galaxy Trucker | 0.016 | no |
2022 | 295770 | Frosthaven | 0.015 | no |
2022 | 240980 | Blood on the Clocktower | 0.014 | no |
2021 | 331685 | Hit the Silk! | 0.014 | no |
2021 | 328859 | Hula-Hoo! | 0.014 | no |
2021 | 346553 | Heuschrecken Poker | 0.013 | no |
2021 | 329714 | Dreadful Circus | 0.013 | no |
2021 | 340677 | Bad Company | 0.013 | no |
2022 | 281647 | Stellaris: Infinite Legacy | 0.013 | no |
2021 | 329450 | Equinox | 0.012 | no |
2021 | 342542 | Less Is More | 0.012 | no |
2021 | 286439 | Import / Export: Definitive Edition | 0.012 | no |
2021 | 344405 | Cartaventura: Oklahoma | 0.011 | no |
2021 | 339789 | Welcome to the Moon | 0.011 | no |
2022 | 271601 | Feed the Kraken | 0.010 | no |
2021 | 337262 | Fangs | 0.010 | no |
2022 | 155250 | TseuQuesT | 0.009 | no |
2021 | 316625 | Cafe Chaos | 0.009 | no |
2022 | 276182 | Dead Reckoning | 0.009 | no |
2021 | 331126 | Scrap Racer | 0.008 | no |
2021 | 340420 | Throw Throw Avocado | 0.008 | no |
2021 | 343696 | Dune: Betrayal | 0.008 | no |
2021 | 307971 | Fairy Tale Inn | 0.008 | no |
2021 | 329529 | Magellan: Elcano | 0.008 | no |
2021 | 326804 | Rorschach | 0.008 | no |
2021 | 337389 | Snakesss | 0.008 | no |
2021 | 326494 | The Adventures of Robin Hood | 0.008 | no |
2022 | 340325 | Vagrantsong | 0.008 | no |
2021 | 262201 | Sword & Sorcery: Ancient Chronicles | 0.008 | no |
2021 | 336195 | League of Dungeoneers | 0.007 | no |